Existing Code Division Multiple Access Systems such as IS-95 and next generation Wideband CDMA (WCDMA) provide multiple user access over radio channels between user terminals such as cellular telephones and base station terminals. The forward link in these systems consists of transmissions from a central station multiple-access transmitter terminal to a multitude of user receiver terminals located within a geographical region or cell. CDMA systems encompass a plurality of cells each with its associated central station. Transmissions to a user receiver terminal may be from more than one central station transmitter thus providing transmit diversity protection. The reverse link in these systems consists of multiple-access transmissions from a multitude of user transmitter terminals located in the cell to a central station receiver terminal. The central station terminal may use multiple antennas for both transmitting and receiving in order to provide diversity protection against multiple-access interference and multipath fading. The user receiver terminal in the forward link may also employ multiple antennas for diversity protection.
CDMA systems may also be combined in a hybrid configuration with Time Division Multiple Access (TDMA) or Frequency Division Multiple Access (FDMA) systems. TDMA shares multiple users in separate time slots, each of which may use CDMA for increased multiple access in the hybrid system. FDMA/CDMA has multiple CDMA subbands.
In CDMA systems users employ a communication signal that occupies the entire CDMA frequency band or subband but the users are assigned different code signatures in order to provide multiple access discrimination between users. The different code signatures are produced by modulating user digital data information with Direct-Sequence Spread Spectrum (DSSS) signals. In this modulation successive digital data symbols representing the transmitted information are multiplied by wider bandwidth DSSS signals. The DSSS signals are periodic pseudonoise (PN) sequences that have N chip symbols for each data symbol, i.e., a DSSS spreading factor of N. The PN sequences have cross correlation properties that protect against other user, i.e., multiple-access, interference and autocorrelation properties that protect against multipath effects. The multipath produces, with respect to the digital data symbols, intersymbol interference (ISI) that degrades quality of data symbol detection. Despite the protection provided by the PN sequence correlation properties, multiple-access and multipath interference limit the capacity of present CDMA systems.
At the central station receiver terminal, a multitude of reverse link users are simultaneously processed to recover the originally transmitted information from each of the user transmitter terminals associated with the central station. This central station processing may be accomplished individually for each user with a group of single-user processors or jointly with one or more subgroups of users employing multiuser processors. The multiuser processors provide joint detection of a set of users so as to reduce multiple-access interference and multipath channel distortions. Because of the physical separation between user terminals, user transmitter terminals may not be mutually time synchronized. For this asynchronous reverse link, the signal components associated with different user terminals are not time aligned in the composite received signal. This lack of synchronism includes misalignment of frames of data containing blocks of digital data symbols and misalignment of the boundaries of the digital data symbols. With symbol misalignment the respective PN sequences are also misaligned and the chosen cross-correlation features are not realized. The asynchronous reverse link application complicates the task of joint detection at the central station receiver.
In the forward link at the user receiver terminal, the information for that user alone must be recovered from one or more received signals that are associated with diversity antennas. These received signals result from transmitted signals at one or more central station transmitter terminals. A single-user processor reduces interference from other users and channel distortion effects such as multipath in recovering the user information. In theory joint processors that generate estimates of other user digital data symbols may also be used in the forward link but in practice computational requirements for mobile user receivers preclude joint-user detection. All the users within a cell may be transmitted from a single central station so that the user component signals at the receiver terminal are time synchronized and have been affected by the same channel. Moreover, the user signals in the forward link may be mutually orthogonal. However, the effects of channel multipath will produce multiple-access interference as well as intersymbol interference. In addition, interfering users may be present that are associated with adjacent cells coming from other central stations. These interfering users produce the same asynchronous adjacent-cell frame and symbol boundary mismatches as in the reverse link application.
For the initial CDMA system, IS-95, the conventional single-user processor included a DSSS matched filter/combiner and RAKE subprocessor. The DSSS matched filter/combiner, so called because its transfer function is matched to the complex conjugate of the user DSSS signal transfer function, reduces the interference from other users by combining chip symbols so as to exploit the cross-correlation properties of the PN sequence in the DSSS signal. The RAKE subprocessor is an adaptive transversal filter that collects or “rakes together” multipath signal returns so as to act as a multipath combiner. These conventional systems, however, do not cancel multiple-access interference or intersymbol interference so that multiuser channel capacity becomes limited by this interference.
Interference compensation or cancellation of multiple-access interference significantly improves multiuser capacity in a CDMA system. The optimum system to combat multiple-access interference is the multiuser Maximum-Likelihood Sequence Estimator (MLSE) described by S. Verdú, “Minimum probability of error for asynchronous Gaussian multiple-access channel”, IEEE Trans. On Inform. Theory, vol. IT-32, no. 1, pp. 85-96, January 1986. Unfortunately the multiuser MLSE increases exponentially in complexity with the number of users and practical application of this technique is limited to a small subset of the users in a CDMA cell.
Equalizers represent a class of suboptimum solutions for multiuser processors. In linear equalization systems, the received signal is decomposed into multiple dimensions corresponding to the user DSSS signals and each dimension is then linearly weighted to reduce multiple-access interference while maximizing the desired user. In Linear Multiuser Detectors for Synchronous Code-Division Multiple Access Channels, R. Lupas and S. Verdu, IEEE Transactions on Information Theory, vol. IT-35, No. 1, pp. 123-136, January 1989, a linear equalization technique called the “decorrelating detector” is shown to reduce multiple-access interference and provide protection when there are both strong and weak user signal strengths. In this article the effects of multipath and methods of adaptation to changing channel conditions are not addressed.
U.S. Pat. No. 5,619,503 describes a multibeam/multiuser cellular system where users are assigned orthogonal frequency/time channels. A linear equalizer is used to reduce interference between users in different cells that are assigned the same orthogonal channel. The linear equalization in U.S. Pat. No. 5,619,503 provides a solution for orthogonal systems such as TDMA or FDMA rather than CDMA and, in addition, does not include intersymbol effects due to asynchronous conditions or multipath.
Equalizers can also include decision-feedback of previous multiuser decisions. In the absence of decision errors a significant performance advantage results relative to linear equalizers. The decision-feedback equalizer (DFE) produces a data symbol estimate by processing received signals and previous decisions derived from detection of previous data symbol estimates. The DFE includes a matched filter, forward filter, and backward filter. The matched filter combines received signals associated with diversity paths and time dimensions. The backward filter processes previous decisions to eliminate past ISI, i.e. ISI due to previous data symbol values. The forward filter processes the matched filter combined signals to reduce interference not cancelled in the backward filter. When the DFE is adapted using a Minimum Mean Square Error (MMSE) criterion there results at the output a balance between the residual interference and enhanced noise thus providing an additional advantage over the decorrelating detector. U.S. Pat. No. 4,328,585 describes a single-user decision-feedback equalizer that includes an adaptive matched filter and a lattice filter realization of the forward and backward filters. An example of a decision-feedback equalizer in the presence of multiple-access interference was given in MMSE Equalization of Interference on Fading Diversity Channels, P. Monsen, IEEE Trans. Commun., vol. COM-32, No. 1, pp. 5-12, January 1984, (hereafter referred to as MMSE Equalization and incorporated herein by reference). In MMSE equalization a minimum mean square (MMSE) DFE was used to reduce both undesired interference and multipath interference for an unknown interference environment, i.e., no knowledge of the transmitted interfering signal parameters was assumed at the receiver. In Decision-Feedback Equalization for CDMA in Indoor Wireless Communications, M. Abdulrahman, A. U. H. Sheikh, and D. D. Falconer, IEEE J. on Selected Areas Commun., vol. 12, pp. 698-707, May 1994, knowledge of only the desired user signal parameters is required. Described results were limited to a four-user system with a DSSS spreading factor of eight. It is intuitive that exploiting the knowledge of the other-user DSSS signals will result in improved interference reduction for those users. A multiuser DFE that includes multiple antennas, asynchronous operation, and exploits knowledge of the in-cell DSSS signal parameters is described in Adaptive Space-Time Feedfoward/Feedback Detection for High Data Rate CDMA in Frequency-Selective Fading, J. E. Smee and S. C. Schwartz, IEEE Trans Commun., vol. 49, No. 2, February 2001. The simulation of this system also employed a spreading factor of eight in which eight users could be supported. Adaptation, however, even with a recursive least squares adaptation algorithm, required a training period of 200 to 500 data symbols for convergence.
Rather than use training sequences or previous decisions to adapt the equalizer as described in the above mentioned prior art, another approach is to attempt to first measure the channel characteristics and then use these characteristics to calculate the equalizer parameters. This technique is generally called block equalization because it operates over a block of data for which it is assumed that the channel is approximately constant. In Channel Equalization for Block Transmission Systems, G. K. Kaleh, IEEE J. on Sel. Areas in Comm., vol. 13, No. 1, January, 1995, zero forcing and MMSE block DFEs are derived for the single dispersive channel with intersymbol interference. The results showed better performance with less complexity for the block method vs. conventional equalization. In another TDMA/FDMA application in Block Channel Equalization in the Presence of a Cochannel Interferent Signal, A. Ginesi, M. Vittetta, and D. D. Falconer, IEEE J. on Sel. Areas of Comm., vol. 17, No. 11, November 1999, a block DFE is derived that combats multipath induced ISI and cochannel interference in the presence of a single interferer. The block DFE is shown to outperform the conventional DFE but at a cost of greater complexity. These block equalization prior art examples do not include techniques to reduce nonstationary channel effects in block equalization. They also do not exploit known interference characteristics such as the PN sequence signatures in CDMA. Block equalization as described in the above articles simultaneously finds estimates for all the symbols in the block so its complexity grows with the block length. In contrast a symbol-by-symbol equalizer can be used to find one symbol estimate after the other within a receiver time block with complexity that grows with the channel duration and not the block length. A block symbol-by-symbol decorrelation detector for a CDMA application is described in On Multipath Channel Estimation for CDMA Systems using Multiple Sensors, C. Sengupta, J. R. Cavallaro, and B. Aazhang, IEEE Trans. On Comm., vol. 49, No. 3, March 2001. The decorrelation detector does not compensate for ISI and results in enhanced noise in the cancellation of the multiple-access interference. In U.S. patent application Ser. No. 09/980,416, filed Feb. 4, 2002, an adaptive processor operating with coding/interleaving is used to reduce multiple-access interference at a multibeam receiver in a synchronous TDMA/FDMA application. Interference is reduced such that orthogonal channels can be reassigned without channel management to achieve 100% reuse of the channel in all beam coverage regions. In one embodiment the adaptive processor is realized with a combination of an adaptive matched filter and a block symbol-by-symbol linear equalizer.
In contrast to a decision-feedback equalizer a decision-feedback detector not only cancels interference from previous decisions of other users but also cancels interference due to the current symbol for some of the users. This technique for interference reduction requires that the other user interference be estimated and subtracted from the received signal in a successive cancellation scheme that eliminates interfering users in a sequence from larger to smaller in received power rank. Examples of these successive cancellation schemes include Decorrelating Decision-Feedback Multiuser Detector for Synchronous Code-Division Multiple Access Channels, A. Duel-Hallen, IEEE Trans. Commun., vol. COM-41, No. 2, pp. 285-290, February 1993, (hereafter denoted as Decorrelating Detector), Adaptive Receiver Structure for Asynchronous CDMA Systems, P. Rapajic and B. Vucetic, IEEE Journal on Selected Areas of Communication, vol. 12, No. 4, pp. 685-697, May 1994, and A Family of Multiuser Decision-Feedback Detectors for Asynchronous Code-Division Multiple Access Channels, A. Duel-Hallen, IEEE Trans. Commun., vol. 42, Nos. 2, 3, 4, February-April 1995. These systems as noted in Decorrelating Detector at page 287, require a rank order of feedback-interference cancellation because “our analysis indicate that feedback is primarily beneficial when interfering users are stronger”. It is anticipated that under conditions when the received signals are about the same level in received power and there are many users, interference estimation errors and subsequent error propagation will preclude successful cancellation with these methods. In a CDMA system with a large number of power controlled users in a reverse link application one would expect many received signal user components to have approximately the same power levels.
For either equalization or successive cancellation techniques, there is a requirement for processing a very large number of parameters. For example if there are K users, D diversity antennas, and M multipath returns per diversity antenna, the equalizer must adapt and process KMD dimensions. In future third generation systems such as WCDMA, typical values for these parameters are K=128, D=2, and M=4 or 1024 dimensions. Although the theoretical solutions for multiuser processors are well known, their application with a large number of dimensions is an open area of research.
In equalization when the number of dimensions are large, the adaptation can be very slow when a conventional least-mean squares (LMS) algorithm is applied. An LMS tracking algorithm for mobile radio channels is described in “Tracking of Time-Varying Mobile Radio Channels. Part I: the Weiner LMS algorithm”, L. Lindbon, M. Sternad, A. Ahlen, IEEE Trans. Commun., vol 49, December 2001. Faster adapting solutions such as Kalman filters require considerably more complexity and are subject to parameter estimation errors. One such technique is described in “Square Root Kalman Filtering for High-Speed Data Received over Fading Dispersive HF Channels”, F. M. Hsu, IEEE Trans.on Info. Theory, vol. 41, no. 4, pp. 944-960, September 1982.
An alternative to large dimension equalization is blind equalization wherein the adaptation does not attempt to track and utilize all dimensions. Examples of blind equalization are given in “Blind Adaptive Multiuser Detection”, M. Honig, U. Madhow, and S. Verdu, IEEE Trans. on Info. Theory, vol. 41, no. 4, pp. 944-960, July 1995, “Performance Analysis of Minimum Variance CDMA Receivers”, M. Tsatsanis and Z. D. Xu, IEEE Trans. on Sig. Processing, vol. 46, no. 11, pp. 3014-3022, November 1998., “Blind Multiuser Detection: a subspace approach”, X. Wang and V. H. Poor, IEEE Trans. on Info Theory, vol. 44, no. 2, pp. 677-690, March 1998. Because of the blind nature of the algorithm, the convergence time can still be long and their resulting performance may be significantly degraded from a solution where the parameters are known or have been accurately estimated.
Next generation systems such as WCDMA will employ larger bandwidths so that both the number of users and the number of multipath interferers will increase relative to present systems. Techniques that cope with multiple-access and multipath interference will require processing of a very large parameter set. Higher data rates used in the next generation systems may have less spread spectrum gain in some applications, so that ISI caused by multipath effects will increase. WCDMA systems will also support multiple data rates further increasing the potential for interference from higher power, higher data rate users into lower power, lower data rate users.
Although the techniques described above have been used for improving quality in multipath fading systems with multiple-access interference, it has been recognized that optimum MLSE techniques are too complex for implementation, decorrelation detectors enhance noise and do not eliminate ISI, techniques that do not exploit known parameters of the interfering signals are limited in performance, successive cancellation techniques have performance limitations due to error propagation, the large number of dimensions in a wideband CDMA application result in performance limitations under changing conditions due to convergence difficulties, and the presence of multiple data rates in WCDMA complicates the task of equalization of mutual interference.